10 citations · 11 across the 10 of their papers we have counts for
11 papers
TwinRouterBench: Fast Static and Live Dynamic Evaluation for Realistic Agentic LLM Routing
Pei Yang, Wanyi Chen, Tongyun Yang +15
LLM routing matters most in long-horizon applications such as coding agents, deep research systems, and computer-use agents, where a single user request triggers many model calls.…
ReCoG: Relational and Compact Context Graph Learning for Few-shot Molecular Property Prediction
Zeyu Wang, Xin Zheng, Yao Lu +3
Few-shot molecular property prediction (FSMPP) is essential in drug discovery and materials design, where high-quality labeled data are often scarce and expensive to obtain. Despit…
Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates
Zeyu Wang, Shuya Yamazaki, Martin Hoffmann Petersen +11
The appearance of generative models has opened vast chemical spaces in the design of functional materials. Although machine learning interatomic potentials (MLIPs) have substantial…
Few-shot Molecular Property Prediction: A Survey
Zeyu Wang, Tianyi Jiang, Huanchang Ma +6
AI-assisted molecular property prediction has become a promising technique in early-stage drug discovery and materials design in recent years. However, due to high-cost and complex…
ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices
Maoyu Wang, Yao Lu, Jiaqi Nie +4
With the rapid development of deep learning, a growing number of pre-trained models have been publicly available. However, deploying these fixed models in real-world IoT applicatio…
FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition
Yao Lu, Tengfei Ma, Zeyu Wang +5
With the rapid development of wireless communications and the growing complexity of digital modulation schemes, traditional manual modulation recognition methods struggle to extrac…
Adaptive Substructure-Aware Expert Model for Molecular Property Prediction
Tianyi Jiang, Zeyu Wang, Shanqing Yu +1
Molecular property prediction is essential for applications such as drug discovery and toxicity assessment. While Graph Neural Networks (GNNs) have shown promising results by model…
Efficient Parallel Genetic Algorithm for Perturbed Substructure Optimization in Complex Network
Shanqing Yu, Meng Zhou, Jintao Zhou +5
Evolutionary computing, particularly genetic algorithm (GA), is a combinatorial optimization method inspired by natural selection and the transmission of genetic information, which…
Reassessing Layer Pruning in LLMs: New Insights and Methods
Yao Lu, Hao Cheng, Yujie Fang +6
Although large language models (LLMs) have achieved remarkable success across various domains, their considerable scale necessitates substantial computational resources, posing sig…
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property Prediction
Zeyu Wang, Tianyi Jiang, Yao Lu +4
Recently, few-shot molecular property prediction (FSMPP) has garnered increasing attention. Despite impressive breakthroughs achieved by existing methods, they often overlook the i…
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry
Zeyu Wang, Tianyi Jiang, Jinhuan Wang +1
Molecular property prediction refers to the task of labeling molecules with some biochemical properties, playing a pivotal role in the drug discovery and design process. Recently,…